1. Field of Invention
The present disclosure relates to an image processing method and a device thereof. More particularly, the present disclosure relates to an image processing method and a device thereof for processing super-resolution images.
2. Description of Related Art
Recently, due to the advancement of display devices, screen sizes of the mobile phones, computers or televisions are getting larger and larger. Moreover, because of the astounding progress in the Internet technology, demand for viewing the images grows rapidly. Since data volumes of normal images are not that small, computation complexity of upscaling the images increases, and the processing time of upscaling the images increases as well.
Normally speaking, common techniques for upscaling images nowadays can be sorted into two groups. One group is based on a database, and the other is based on interpolation. The group, which is based on the database, normally requires a huge amount of low-resolution images and the corresponding high-resolution images. Both the low-resolution images and the high-resolution images are stored in the database. While an user is increasing the resolution of a low-resolution image, the low-resolution image is divided into multiple blocks, and each of the blocks is compared with the low-resolution images stored in the database. When one of the blocks is similar to one of the low-resolution images in the database, the high-resolution image corresponding to the one of the low-resolution images is allocated to a block corresponding to the one of the blocks. Therefore, the group based on the database requires long processing time and large storage capacity, which is not suitable for the device having limited resources.
On the other hand, the other group based on the interpolation method requires less hardware resources. The image upscaling techniques based on interpolation normally start with upsampling of the image. Then, the upsampled image is interpolated by an interpolation algorithm. However, although the techniques based on interpolation achieve faster processing speed, low distortion of the upscaled images is still not stably achieved.
Therefore, under the circumstance with limited hardware resource, there is still a need for a more efficient algorithm so as to increase the processing speed and maintain the quality.